Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations1300
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.2 KiB
Average record size in memory104.1 B

Variable types

Numeric8
Categorical5

Alerts

id is highly overall correlated with Покупательская активность and 1 other fieldsHigh correlation
Покупательская активность is highly overall correlated with id and 1 other fieldsHigh correlation
Страниц_за_визит is highly overall correlated with id and 1 other fieldsHigh correlation
id is uniformly distributed Uniform
id has unique values Unique
Неоплаченные_продукты_штук_квартал has 116 (8.9%) zeros Zeros
Ошибка_сервиса has 17 (1.3%) zeros Zeros

Reproduction

Analysis started2025-10-07 14:12:52.262896
Analysis finished2025-10-07 14:13:19.953741
Duration27.69 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

id
Real number (ℝ)

High correlation  Uniform  Unique 

Distinct1300
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215997.5
Minimum215348
Maximum216647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:20.287191image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum215348
5-th percentile215412.95
Q1215672.75
median215997.5
Q3216322.25
95-th percentile216582.05
Maximum216647
Range1299
Interquartile range (IQR)649.5

Descriptive statistics

Standard deviation375.42198
Coefficient of variation (CV)0.0017380849
Kurtosis-1.2
Mean215997.5
Median Absolute Deviation (MAD)325
Skewness0
Sum2.8079675 × 108
Variance140941.67
MonotonicityStrictly increasing
2025-10-07T19:13:21.271119image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
216647 1
 
0.1%
215348 1
 
0.1%
215349 1
 
0.1%
215350 1
 
0.1%
216631 1
 
0.1%
216630 1
 
0.1%
216629 1
 
0.1%
216628 1
 
0.1%
216627 1
 
0.1%
216626 1
 
0.1%
Other values (1290) 1290
99.2%
ValueCountFrequency (%)
215348 1
0.1%
215349 1
0.1%
215350 1
0.1%
215351 1
0.1%
215352 1
0.1%
215353 1
0.1%
215354 1
0.1%
215355 1
0.1%
215356 1
0.1%
215357 1
0.1%
ValueCountFrequency (%)
216647 1
0.1%
216646 1
0.1%
216645 1
0.1%
216644 1
0.1%
216643 1
0.1%
216642 1
0.1%
216641 1
0.1%
216640 1
0.1%
216639 1
0.1%
216638 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
Прежний уровень
802 
Снизилась
498 

Length

Max length15
Median length15
Mean length12.701538
Min length9

Characters and Unicode

Total characters16512
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowСнизилась
2nd rowСнизилась
3rd rowСнизилась
4th rowСнизилась
5th rowСнизилась

Common Values

ValueCountFrequency (%)
Прежний уровень 802
61.7%
Снизилась 498
38.3%

Length

2025-10-07T19:13:21.886871image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-07T19:13:22.251089image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
прежний 802
38.2%
уровень 802
38.2%
снизилась 498
23.7%

Most occurring characters

ValueCountFrequency (%)
н 2102
12.7%
и 1798
10.9%
е 1604
 
9.7%
р 1604
 
9.7%
ь 1300
 
7.9%
П 802
 
4.9%
ж 802
 
4.9%
802
 
4.9%
й 802
 
4.9%
у 802
 
4.9%
Other values (7) 4094
24.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16512
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
н 2102
12.7%
и 1798
10.9%
е 1604
 
9.7%
р 1604
 
9.7%
ь 1300
 
7.9%
П 802
 
4.9%
ж 802
 
4.9%
802
 
4.9%
й 802
 
4.9%
у 802
 
4.9%
Other values (7) 4094
24.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16512
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
н 2102
12.7%
и 1798
10.9%
е 1604
 
9.7%
р 1604
 
9.7%
ь 1300
 
7.9%
П 802
 
4.9%
ж 802
 
4.9%
802
 
4.9%
й 802
 
4.9%
у 802
 
4.9%
Other values (7) 4094
24.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16512
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
н 2102
12.7%
и 1798
10.9%
е 1604
 
9.7%
р 1604
 
9.7%
ь 1300
 
7.9%
П 802
 
4.9%
ж 802
 
4.9%
802
 
4.9%
й 802
 
4.9%
у 802
 
4.9%
Other values (7) 4094
24.8%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
стандарт
914 
премиум
376 
стандартт
 
10

Length

Max length9
Median length8
Mean length7.7184615
Min length7

Characters and Unicode

Total characters10034
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowпремиум
2nd rowпремиум
3rd rowстандартт
4th rowстандартт
5th rowстандартт

Common Values

ValueCountFrequency (%)
стандарт 914
70.3%
премиум 376
28.9%
стандартт 10
 
0.8%

Length

2025-10-07T19:13:22.621906image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-07T19:13:22.978700image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
стандарт 914
70.3%
премиум 376
28.9%
стандартт 10
 
0.8%

Most occurring characters

ValueCountFrequency (%)
т 1858
18.5%
а 1848
18.4%
р 1300
13.0%
с 924
9.2%
н 924
9.2%
д 924
9.2%
м 752
7.5%
п 376
 
3.7%
е 376
 
3.7%
и 376
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10034
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
т 1858
18.5%
а 1848
18.4%
р 1300
13.0%
с 924
9.2%
н 924
9.2%
д 924
9.2%
м 752
7.5%
п 376
 
3.7%
е 376
 
3.7%
и 376
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10034
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
т 1858
18.5%
а 1848
18.4%
р 1300
13.0%
с 924
9.2%
н 924
9.2%
д 924
9.2%
м 752
7.5%
п 376
 
3.7%
е 376
 
3.7%
и 376
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10034
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
т 1858
18.5%
а 1848
18.4%
р 1300
13.0%
с 924
9.2%
н 924
9.2%
д 924
9.2%
м 752
7.5%
п 376
 
3.7%
е 376
 
3.7%
и 376
 
3.7%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
да
962 
нет
338 

Length

Max length3
Median length2
Mean length2.26
Min length2

Characters and Unicode

Total characters2938
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowда
2nd rowда
3rd rowнет
4th rowда
5th rowнет

Common Values

ValueCountFrequency (%)
да 962
74.0%
нет 338
 
26.0%

Length

2025-10-07T19:13:23.355693image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-07T19:13:23.691984image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
да 962
74.0%
нет 338
 
26.0%

Most occurring characters

ValueCountFrequency (%)
д 962
32.7%
а 962
32.7%
н 338
 
11.5%
е 338
 
11.5%
т 338
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2938
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
д 962
32.7%
а 962
32.7%
н 338
 
11.5%
е 338
 
11.5%
т 338
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2938
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
д 962
32.7%
а 962
32.7%
н 338
 
11.5%
е 338
 
11.5%
т 338
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2938
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
д 962
32.7%
а 962
32.7%
н 338
 
11.5%
е 338
 
11.5%
т 338
 
11.5%
Distinct41
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2537692
Minimum0.9
Maximum6.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:24.106338image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile2.4
Q13.7
median4.2
Q34.9
95-th percentile5.8
Maximum6.6
Range5.7
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.0148139
Coefficient of variation (CV)0.23856816
Kurtosis0.62060502
Mean4.2537692
Median Absolute Deviation (MAD)0.7
Skewness-0.44478178
Sum5529.9
Variance1.0298472
MonotonicityNot monotonic
2025-10-07T19:13:24.785039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
4.1 94
 
7.2%
3.9 83
 
6.4%
4.4 82
 
6.3%
4 71
 
5.5%
5.5 68
 
5.2%
4.3 66
 
5.1%
4.9 60
 
4.6%
3.5 50
 
3.8%
4.6 49
 
3.8%
3.3 47
 
3.6%
Other values (31) 630
48.5%
ValueCountFrequency (%)
0.9 11
 
0.8%
1.4 5
 
0.4%
1.5 8
 
0.6%
1.7 12
 
0.9%
2.4 42
3.2%
2.6 20
1.5%
2.7 8
 
0.6%
2.9 7
 
0.5%
3 16
 
1.2%
3.1 16
 
1.2%
ValueCountFrequency (%)
6.6 12
 
0.9%
6.3 12
 
0.9%
6.1 12
 
0.9%
5.9 5
 
0.4%
5.8 27
 
2.1%
5.7 28
2.2%
5.6 25
 
1.9%
5.5 68
5.2%
5.4 23
 
1.8%
5.3 27
 
2.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
4
669 
5
323 
3
308 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1300
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row4
3rd row3
4th row5
5th row3

Common Values

ValueCountFrequency (%)
4 669
51.5%
5 323
24.8%
3 308
23.7%

Length

2025-10-07T19:13:25.403514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-07T19:13:25.736516image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
4 669
51.5%
5 323
24.8%
3 308
23.7%

Most occurring characters

ValueCountFrequency (%)
4 669
51.5%
5 323
24.8%
3 308
23.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1300
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 669
51.5%
5 323
24.8%
3 308
23.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1300
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 669
51.5%
5 323
24.8%
3 308
23.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1300
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 669
51.5%
5 323
24.8%
3 308
23.7%

Длительность
Real number (ℝ)

Distinct658
Distinct (%)50.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean601.89846
Minimum110
Maximum1079
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:26.228189image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile184
Q1405.5
median606
Q3806
95-th percentile997.05
Maximum1079
Range969
Interquartile range (IQR)400.5

Descriptive statistics

Standard deviation249.85629
Coefficient of variation (CV)0.41511369
Kurtosis-0.99301711
Mean601.89846
Median Absolute Deviation (MAD)200
Skewness-0.062817461
Sum782468
Variance62428.165
MonotonicityNot monotonic
2025-10-07T19:13:26.778280image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449 7
 
0.5%
627 7
 
0.5%
600 7
 
0.5%
511 6
 
0.5%
666 6
 
0.5%
503 6
 
0.5%
684 6
 
0.5%
475 6
 
0.5%
509 6
 
0.5%
788 6
 
0.5%
Other values (648) 1237
95.2%
ValueCountFrequency (%)
110 1
 
0.1%
121 4
0.3%
125 1
 
0.1%
129 2
0.2%
131 1
 
0.1%
132 1
 
0.1%
133 1
 
0.1%
134 1
 
0.1%
135 1
 
0.1%
136 3
0.2%
ValueCountFrequency (%)
1079 1
0.1%
1076 1
0.1%
1073 1
0.1%
1072 1
0.1%
1065 1
0.1%
1064 1
0.1%
1061 2
0.2%
1057 2
0.2%
1056 1
0.1%
1052 1
0.1%
Distinct42
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.31980769
Minimum0
Maximum0.99
Zeros3
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:27.284918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13
Q10.17
median0.24
Q30.3
95-th percentile0.95
Maximum0.99
Range0.99
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.24984314
Coefficient of variation (CV)0.7812293
Kurtosis2.1774728
Mean0.31980769
Median Absolute Deviation (MAD)0.07
Skewness1.8953925
Sum415.75
Variance0.062421595
MonotonicityNot monotonic
2025-10-07T19:13:27.810432image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.24 93
 
7.2%
0.3 85
 
6.5%
0.28 83
 
6.4%
0.17 79
 
6.1%
0.25 72
 
5.5%
0.14 69
 
5.3%
0.13 64
 
4.9%
0.21 64
 
4.9%
0.16 62
 
4.8%
0.23 60
 
4.6%
Other values (32) 569
43.8%
ValueCountFrequency (%)
0 3
 
0.2%
0.11 31
 
2.4%
0.12 20
 
1.5%
0.13 64
4.9%
0.14 69
5.3%
0.15 49
3.8%
0.16 62
4.8%
0.17 79
6.1%
0.18 23
 
1.8%
0.19 11
 
0.8%
ValueCountFrequency (%)
0.99 30
2.3%
0.98 17
 
1.3%
0.95 24
1.8%
0.94 43
3.3%
0.93 19
1.5%
0.91 5
 
0.4%
0.9 11
 
0.8%
0.89 16
 
1.2%
0.75 1
 
0.1%
0.74 1
 
0.1%
Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
Товары для детей
330 
Домашний текстиль
251 
Косметика и аксесуары
223 
Техника для красоты и здоровья
184 
Мелкая бытовая техника и электроника
174 

Length

Max length36
Median length21
Mean length21.603077
Min length15

Characters and Unicode

Total characters28084
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowТовары для детей
2nd rowТовары для детей
3rd rowДомашний текстиль
4th rowТовары для детей
5th rowТовары для детей

Common Values

ValueCountFrequency (%)
Товары для детей 330
25.4%
Домашний текстиль 251
19.3%
Косметика и аксесуары 223
17.2%
Техника для красоты и здоровья 184
14.2%
Мелкая бытовая техника и электроника 174
13.4%
Кухонная посуда 138
10.6%

Length

2025-10-07T19:13:28.252829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-07T19:13:28.919765image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
и 581
13.7%
для 514
12.2%
техника 358
 
8.5%
детей 330
 
7.8%
товары 330
 
7.8%
домашний 251
 
5.9%
текстиль 251
 
5.9%
косметика 223
 
5.3%
аксесуары 223
 
5.3%
красоты 184
 
4.4%
Other values (6) 982
23.2%

Most occurring characters

ValueCountFrequency (%)
2927
 
10.4%
а 2590
 
9.2%
е 2063
 
7.3%
о 1980
 
7.1%
и 1838
 
6.5%
к 1761
 
6.3%
т 1761
 
6.3%
с 1242
 
4.4%
я 1184
 
4.2%
д 1166
 
4.2%
Other values (19) 9572
34.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28084
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2927
 
10.4%
а 2590
 
9.2%
е 2063
 
7.3%
о 1980
 
7.1%
и 1838
 
6.5%
к 1761
 
6.3%
т 1761
 
6.3%
с 1242
 
4.4%
я 1184
 
4.2%
д 1166
 
4.2%
Other values (19) 9572
34.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28084
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2927
 
10.4%
а 2590
 
9.2%
е 2063
 
7.3%
о 1980
 
7.1%
и 1838
 
6.5%
к 1761
 
6.3%
т 1761
 
6.3%
с 1242
 
4.4%
я 1184
 
4.2%
д 1166
 
4.2%
Other values (19) 9572
34.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28084
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2927
 
10.4%
а 2590
 
9.2%
е 2063
 
7.3%
о 1980
 
7.1%
и 1838
 
6.5%
к 1761
 
6.3%
т 1761
 
6.3%
с 1242
 
4.4%
я 1184
 
4.2%
д 1166
 
4.2%
Other values (19) 9572
34.1%
Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.27
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:29.710480image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3553504
Coefficient of variation (CV)0.41448023
Kurtosis-0.70012882
Mean3.27
Median Absolute Deviation (MAD)1
Skewness0.27330771
Sum4251
Variance1.8369746
MonotonicityNot monotonic
2025-10-07T19:13:30.074694image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 356
27.4%
2 312
24.0%
4 263
20.2%
5 177
13.6%
1 106
 
8.2%
6 86
 
6.6%
ValueCountFrequency (%)
1 106
 
8.2%
2 312
24.0%
3 356
27.4%
4 263
20.2%
5 177
13.6%
6 86
 
6.6%
ValueCountFrequency (%)
6 86
 
6.6%
5 177
13.6%
4 263
20.2%
3 356
27.4%
2 312
24.0%
1 106
 
8.2%
Distinct11
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.84
Minimum0
Maximum10
Zeros116
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:30.427171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile7
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9714514
Coefficient of variation (CV)0.69417302
Kurtosis0.45521388
Mean2.84
Median Absolute Deviation (MAD)1
Skewness0.76682589
Sum3692
Variance3.8866205
MonotonicityNot monotonic
2025-10-07T19:13:30.868068image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 261
20.1%
1 261
20.1%
3 218
16.8%
4 197
15.2%
5 135
10.4%
0 116
8.9%
6 44
 
3.4%
7 34
 
2.6%
8 20
 
1.5%
9 10
 
0.8%
ValueCountFrequency (%)
0 116
8.9%
1 261
20.1%
2 261
20.1%
3 218
16.8%
4 197
15.2%
5 135
10.4%
6 44
 
3.4%
7 34
 
2.6%
8 20
 
1.5%
9 10
 
0.8%
ValueCountFrequency (%)
10 4
 
0.3%
9 10
 
0.8%
8 20
 
1.5%
7 34
 
2.6%
6 44
 
3.4%
5 135
10.4%
4 197
15.2%
3 218
16.8%
2 261
20.1%
1 261
20.1%

Ошибка_сервиса
Real number (ℝ)

Zeros 

Distinct10
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1853846
Minimum0
Maximum9
Zeros17
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:31.252700image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q36
95-th percentile8
Maximum9
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9552976
Coefficient of variation (CV)0.46717275
Kurtosis-0.51036217
Mean4.1853846
Median Absolute Deviation (MAD)1
Skewness0.25214048
Sum5441
Variance3.8231888
MonotonicityNot monotonic
2025-10-07T19:13:31.617840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 257
19.8%
3 226
17.4%
5 208
16.0%
2 189
14.5%
6 156
12.0%
7 92
 
7.1%
1 74
 
5.7%
8 66
 
5.1%
0 17
 
1.3%
9 15
 
1.2%
ValueCountFrequency (%)
0 17
 
1.3%
1 74
 
5.7%
2 189
14.5%
3 226
17.4%
4 257
19.8%
5 208
16.0%
6 156
12.0%
7 92
 
7.1%
8 66
 
5.1%
9 15
 
1.2%
ValueCountFrequency (%)
9 15
 
1.2%
8 66
 
5.1%
7 92
 
7.1%
6 156
12.0%
5 208
16.0%
4 257
19.8%
3 226
17.4%
2 189
14.5%
1 74
 
5.7%
0 17
 
1.3%

Страниц_за_визит
Real number (ℝ)

High correlation 

Distinct20
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1769231
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2025-10-07T19:13:31.996379image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median8
Q311
95-th percentile15
Maximum20
Range19
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.9781261
Coefficient of variation (CV)0.48650648
Kurtosis-0.52970033
Mean8.1769231
Median Absolute Deviation (MAD)3
Skewness0.36781673
Sum10630
Variance15.825487
MonotonicityNot monotonic
2025-10-07T19:13:32.510063image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
6 127
9.8%
5 115
8.8%
4 112
 
8.6%
8 109
 
8.4%
9 108
 
8.3%
10 104
 
8.0%
7 102
 
7.8%
11 92
 
7.1%
3 76
 
5.8%
12 73
 
5.6%
Other values (10) 282
21.7%
ValueCountFrequency (%)
1 20
 
1.5%
2 58
4.5%
3 76
5.8%
4 112
8.6%
5 115
8.8%
6 127
9.8%
7 102
7.8%
8 109
8.4%
9 108
8.3%
10 104
8.0%
ValueCountFrequency (%)
20 2
 
0.2%
19 5
 
0.4%
18 7
 
0.5%
17 19
 
1.5%
16 21
 
1.6%
15 36
 
2.8%
14 53
4.1%
13 61
4.7%
12 73
5.6%
11 92
7.1%

Interactions

2025-10-07T19:13:15.363643image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:54.244987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:57.290419image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:00.145309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:02.914926image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:06.078045image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:09.262064image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:12.357377image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:15.685893image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:54.581873image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:57.593216image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:00.447774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:03.268786image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:06.405241image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:09.607813image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:12.704304image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:16.002094image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:54.940897image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:57.885275image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:00.880141image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:03.839987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:06.691099image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:09.976370image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:13.009572image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:16.316160image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:55.436192image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:58.425579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:01.386932image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:04.371086image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:07.037138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:10.308231image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:13.310168image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:16.644280image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:55.978975image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:58.842232image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:01.762136image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:04.674777image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:07.384451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:10.643679image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:13.611482image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:16.988505image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:56.294235image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:59.222535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:02.047435image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:04.980030image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:08.036812image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:10.984169image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:13.961933image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:17.361047image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:56.626040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:59.535695image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:02.331323image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:05.295181image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:08.502987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:11.544689image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:14.458738image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:18.108799image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:56.953780image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:12:59.811476image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:02.594443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:05.754474image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:08.876601image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:11.985274image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-10-07T19:13:14.979563image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2025-10-07T19:13:33.068630image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
idАкционные_покупкиДлительностьМаркет_актив_6_месМаркет_актив_тек_месНеоплаченные_продукты_штук_кварталОшибка_сервисаПокупательская активностьПопулярная_категорияРазрешить сообщатьСредний_просмотр_категорий_за_визитСтраниц_за_визитТип сервиса
id1.000-0.370-0.0550.3410.000-0.2550.0980.8890.0920.0000.2760.5300.172
Акционные_покупки-0.3701.0000.036-0.2750.0040.198-0.0510.4990.0510.000-0.205-0.3650.126
Длительность-0.0550.0361.000-0.0430.107-0.1080.1030.0690.0000.190-0.046-0.0300.218
Маркет_актив_6_мес0.341-0.275-0.0431.0000.046-0.1340.0390.4200.0790.0000.1840.3200.027
Маркет_актив_тек_мес0.0000.0040.1070.0461.0000.0870.0690.0000.0550.0870.1050.0000.046
Неоплаченные_продукты_штук_квартал-0.2550.198-0.108-0.1340.0871.000-0.0970.3860.1330.150-0.252-0.1650.055
Ошибка_сервиса0.098-0.0510.1030.0390.069-0.0971.0000.1680.0000.0000.0080.1040.087
Покупательская активность0.8890.4990.0690.4200.0000.3860.1681.0000.2130.0000.3870.5880.128
Популярная_категория0.0920.0510.0000.0790.0550.1330.0000.2131.0000.0510.0830.0840.012
Разрешить сообщать0.0000.0000.1900.0000.0870.1500.0000.0000.0511.0000.0520.0340.185
Средний_просмотр_категорий_за_визит0.276-0.205-0.0460.1840.105-0.2520.0080.3870.0830.0521.0000.2650.088
Страниц_за_визит0.530-0.365-0.0300.3200.000-0.1650.1040.5880.0840.0340.2651.0000.078
Тип сервиса0.1720.1260.2180.0270.0460.0550.0870.1280.0120.1850.0880.0781.000

Missing values

2025-10-07T19:13:18.845306image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-07T19:13:19.607217image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

idПокупательская активностьТип сервисаРазрешить сообщатьМаркет_актив_6_месМаркет_актив_тек_месДлительностьАкционные_покупкиПопулярная_категорияСредний_просмотр_категорий_за_визитНеоплаченные_продукты_штук_кварталОшибка_сервисаСтраниц_за_визит
0215348Снизиласьпремиумда3.451210.00Товары для детей6215
1215349Снизиласьпремиумда4.448190.75Товары для детей4425
2215350Снизиласьстандарттнет4.935390.14Домашний текстиль5215
3215351Снизиласьстандарттда3.258960.99Товары для детей5064
4215352Снизиласьстандарттнет5.1310640.94Товары для детей3232
5215353Снизиласьстандарттда3.347620.26Домашний текстиль4114
6215354Снизиласьстандарттда5.134310.23Косметика и аксесуары2372
7215355Снизиласьстандарттнет4.742840.17Товары для детей5164
8215356Снизиласьстандарттда4.241920.14Косметика и аксесуары2213
9215357Снизиласьстандарттда3.951540.00Техника для красоты и здоровья3395
idПокупательская активностьТип сервисаРазрешить сообщатьМаркет_актив_6_месМаркет_актив_тек_месДлительностьАкционные_покупкиПопулярная_категорияСредний_просмотр_категорий_за_визитНеоплаченные_продукты_штук_кварталОшибка_сервисаСтраниц_за_визит
1290216638Прежний уровеньстандартнет1.539300.29Мелкая бытовая техника и электроника20416
1291216639Прежний уровеньстандартда4.843060.29Товары для детей4537
1292216640Прежний уровеньстандартнет5.744160.95Кухонная посуда23513
1293216641Прежний уровеньстандартда4.146380.22Техника для красоты и здоровья41614
1294216642Прежний уровеньпремиумда4.239910.40Мелкая бытовая техника и электроника43512
1295216643Прежний уровеньстандартда6.633180.24Техника для красоты и здоровья53311
1296216644Прежний уровеньстандартнет5.144540.21Домашний текстиль6239
1297216645Прежний уровеньстандартда4.135860.20Домашний текстиль3257
1298216646Прежний уровеньстандартда6.356450.12Техника для красоты и здоровья3357
1299216647Прежний уровеньпремиумда4.059060.94Техника для красоты и здоровья45312